How to filter rows in pandas by regex

Question

I would like to cleanly filter a dataframe using regex on one of the columns.

For a contrived example:

In [210]: foo = pd.DataFrame({'a' : [1,2,3,4], 'b' : ['hi', 'foo', 'fat', 'cat']})
In [211]: foo
Out[211]: 
   a    b
0  1   hi
1  2  foo
2  3  fat
3  4  cat

I want to filter the rows to those that start with f using a regex. First go:

In [213]: foo.b.str.match('f.*')
Out[213]: 
0    []
1    ()
2    ()
3    []

That's not too terribly useful. However this will get me my boolean index:

In [226]: foo.b.str.match('(f.*)').str.len() > 0
Out[226]: 
0    False
1     True
2     True
3    False
Name: b

So I could then do my restriction by:

In [229]: foo[foo.b.str.match('(f.*)').str.len() > 0]
Out[229]: 
   a    b
1  2  foo
2  3  fat

That makes me artificially put a group into the regex though, and seems like maybe not the clean way to go. Is there a better way to do this?

Answer 1

Use contains instead:

In [10]: df.b.str.contains('^f')
Out[10]: 
0    False
1     True
2     True
3    False
Name: b, dtype: bool